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Impacto da inteligência artificial na triagem do câncer de mama

5 de novembro de 2026 atualizado por: Jonsson Comprehensive Cancer Center

Avaliando o impacto da inteligência artificial na qualidade e na eficácia da triagem de câncer de mama: um estudo prospectivo randomizado controlado

The goal of this clinical trial is to compare patient-centered outcomes when screening digital breast tomosynthesis (DBT) exams are interpreted with versus without a leading FDA-cleared artificial intelligence (AI) decision-support tool in real-world U.S. settings and to assess patients' and radiologists' perspectives on AI in medicine.

The main question it aims to answer is: Does an FDA-cleared AI decision-support tool for digital tomosynthesis (DBT) improve screening outcomes in real world US clinical settings?

This trial will include all interpreting radiologists and all adult patients undergoing screening mammography at any of the participating breast imaging facilities across 6 regional health systems (University of California, Los Angeles (UCLA), University of California, San Diego (UCSD), University of Washington-Seattle, University of Wisconsin-Madison, Boston Medical Center, and University of Miami) during the trial period.

All screening mammograms at these facilities will be randomized to either intervention (radiologist assisted by an AI decision support tool) versus usual care (radiologist alone) to see if interpreting these mammograms with the AI tool's assistance improves patient screening outcomes.

We are targeting 400,000 screening exams across the participating health systems in this trial.

Visão geral do estudo

Status

Recrutamento

Condições

Intervenção / Tratamento

Descrição detalhada

During the RCT the AI support tool will be randomized to be turned on or off (1:1) at the mammography exam level. Patients who return for screening exams in year 2 of recruitment will be randomized again (e.g., they will not retain their prior randomization). Radiologists will not be able to sort exams based on AI availability or AI scores. Randomizing by exam level will ensure that we capture a substantial number of interpretations with vs. without AI for each radiologist, allowing for quantification of the radiologist-level AI learning curve. We are not randomizing at the facility level as some radiologists interpret exams acquired at different facilities on the same day. By randomizing AI at the exam level, we will have the best ability to estimate and adjust for temporal trends in screening outcomes across individual radiologists. Randomization across large regional health systems will be managed independently at each participating site.

Our RCT randomizes screening mammography exams to be interpreted either with or without an AI decision-support tool. As a result, radiologists cannot be blinded to study arm during screening mammography interpretation. However, interpreting radiologists and facility staff (e.g., those scheduling the exams) will not know in advance which patients will be randomized to the AI tool. Randomization occurs within minutes after the breast imaging acquisition (i.e., when the mammography technologist captures the images) by an automated system that was developed by a third-party AI platform and successfully piloted at UCLA. Thus, the AI data (or lack thereof) is embedded within the mammogram before the radiologist opens the exam, preventing any option to "add AI" to an exam randomized to be interpreted without AI. Radiologists will be aware of AI availability only at the time of interpretation, as AI information will appear upon opening the exam (e.g., the AI information pops up with the exam images).

Tipo de estudo

Intervencional

Inscrição (Estimado)

400000

Estágio

  • Fase 4

Contactos e Locais

Esta seção fornece os detalhes de contato para aqueles que conduzem o estudo e informações sobre onde este estudo está sendo realizado.

Contato de estudo

Locais de estudo

    • California
      • Los Angeles, California, Estados Unidos, 90024
        • Recrutamento
        • University of California Los Angeles Health System
        • Investigador principal:
          • Hannah S. Milch, MD
        • Contato:
        • Investigador principal:
          • Joann G Elmore, MD, MPH
      • San Diego, California, Estados Unidos, 92093
        • Recrutamento
        • University of California, San Diego
        • Investigador principal:
          • Haydee Ojeda-Fournier, MD
        • Contato:
    • Florida
      • Miami, Florida, Estados Unidos, 33136
        • Recrutamento
        • University of Miami Health System
        • Contato:
        • Investigador principal:
          • Jose Net, MD
    • Massachusetts
      • Boston, Massachusetts, Estados Unidos, 02118
        • Recrutamento
        • Boston Medical Center
        • Contato:
        • Investigador principal:
          • Clare Poynton, MD, PhD
    • Washington
      • Seattle, Washington, Estados Unidos, 98195
        • Recrutamento
        • University of Washington Health System
        • Contato:
        • Investigador principal:
          • Janie Lee, MD, MSc
    • Wisconsin
      • Madison, Wisconsin, Estados Unidos, 53706
        • Recrutamento
        • University of Wisconsin-Madison
        • Contato:
        • Investigador principal:
          • Christoph Lee, MD, MSc

Critérios de participação

Os pesquisadores procuram pessoas que se encaixem em uma determinada descrição, chamada de critérios de elegibilidade. Alguns exemplos desses critérios são a condição geral de saúde de uma pessoa ou tratamentos anteriores.

Critérios de elegibilidade

Idades elegíveis para estudo

18 anos e mais velhos (Adulto, Adulto mais velho)

Aceita Voluntários Saudáveis

Sim

Gêneros Elegíveis para o Estudo

Tudo

Descrição

This trial will include all radiologists interpreting screening mammography and all adult patients undergoing screening mammography at any of the participating breast imaging facilities across 6 regional health systems (UCLA, UC San Diego, University of Washington-Seattle, University of Wisconsin-Madison, Boston Medical Center, and University of Miami) during the trial period. Individuals must meet the following eligiblity criteria.

Inclusion Criteria:

  1. Be at least 18 years of age or older
  2. Receive a screening mammogram at one of the participating breast imaging facilities OR be a radiologist who interprets screening mammograms at one of the participating breast imaging facilities.

Exclusion Criteria:

1. Patients who have opted out of all research at the health system

Plano de estudo

Esta seção fornece detalhes do plano de estudo, incluindo como o estudo é projetado e o que o estudo está medindo.

Como o estudo é projetado?

Detalhes do projeto

  • Finalidade Principal: Triagem
  • Alocação: Randomizado
  • Modelo Intervencional: Atribuição Paralela
  • Mascaramento: Solteiro

Armas e Intervenções

Grupo de Participantes / Braço
Intervenção / Tratamento
Comparador Ativo: Intervention (radiologist assisted by AI)

3D screening exams randomized to this arm will be interpreted by the radiologist assisted by the AI decision-support tool (i.e., intervention).

The intervention is an AI decision-support tool to help radiologists interpret 3D screening mammograms. For exams randomized to this intervention arm, the first image displayed to the radiologist upon opening an exam on the viewing station will be a one-page, standardized AI report showing the overall exam risk (elevated, intermediate, or low), image region markings, lesion scores from 1-100 (100 being the highest suspicion), bounding boxes, and relevant slice locations for 3D exams. Radiologists can toggle markings on/off and retain full control over the final interpretation of the exam as positive or negative (i.e., they can choose to ignore the AI information).

Randomization occurs 1:1 at the exam level via automated code at image acquisition. Returning patients in year two will be re-randomized. Radiologists cannot filter their exam lists by AI availability or risk, and randomization will be independently managed at each participating health system.

Sem intervenção: Standard care (radiologist alone)

3D screening exams randomized to this arm will be interpreted in accordance with standard care (i.e., interpreted by the radiologist alone, without an AI decision-support tool's assistance).

O que o estudo está medindo?

Medidas de resultados primários

Medida de resultado
Descrição da medida
Prazo
Cancer detection rate
Prazo: Cancer diagnosed within 90 days of positive study entry screening mammogram

Number of screening exams recommended for breast biopsy (final Breast Imaging- Reporting and Data System [BI-RADS] assessment of 4 or 5) resulting in detected cancer, per 1,000 screening exams

Cancer diagnosed within 90 days of positive study entry screening mammogram
Recall rate
Prazo: Through study completion, an average of 1 year

Number of screening exams recalled for diagnostic work-up (initial BI-RADS assessment of 0, 3, 4, or 5), per 1,000 screening exams

Through study completion, an average of 1 year

Medidas de resultados secundários

Medida de resultado
Descrição da medida
Prazo
Interval cancer rate (i.e., false-negative rate)
Prazo: Cancer diagnosed within 365 days of a negative study entry screening mammogram

Number of screening exams with a negative assessment (final BI-RADS assessment of 1 or 2) and breast cancer diagnosed within 1 year, per 1,000 screening exams

Cancer diagnosed within 365 days of a negative study entry screening mammogram
False positive recall rate
Prazo: No cancer diagnosed within 365 days of a positive study entry screening mammogram

Proportion of screening exams recalled for additional imaging (final BI-RADS assessment of 1, 2, or 3), with no breast cancer diagnosed within 1 year

No cancer diagnosed within 365 days of a positive study entry screening mammogram
False positive short-interval follow-up recommendation rate
Prazo: No cancer diagnosed within 365 days of a positive study entry screening mammogram

Proportion of screening exams recalled for short-interval follow-up (final BI-RADS assessment of 3) with no breast cancer diagnosed within 1 year

No cancer diagnosed within 365 days of a positive study entry screening mammogram
False positive biopsy recommendation rate
Prazo: No cancer diagnosed within 365 days of a positive study entry screening mammogram

Proportion of screening exams recalled for breast biopsy (final BI-RADS assessment of 4 or 5) with no breast cancer diagnosed within 1 year

No cancer diagnosed within 365 days of a positive study entry screening mammogram
Trust and confidence in AI
Prazo: Years 1,2 and Years 4,5

Trust and confidence in AI gathered from focus group and survey data

Years 1,2 and Years 4,5
Efficiency metrics (only for the UCLA site)
Prazo: Through study completion, an average of 1 year

Interpretation time required for radiologists to interpret each mammogram with versus without AI.

Delivery time, using time stamp data from exam acquisition to delivery of results to patients (aka turnaround time).

Through study completion, an average of 1 year

Colaboradores e Investigadores

É aqui que você encontrará pessoas e organizações envolvidas com este estudo.

Patrocinador

Colaboradores

Investigadores

  • Investigador principal: Diana Miglioretti, PhD, University of California, Davis
  • Investigador principal: Joann G Elmore, MD, MPH, University of California, Los Angeles

Datas de registro do estudo

Essas datas acompanham o progresso do registro do estudo e os envios de resumo dos resultados para ClinicalTrials.gov. Os registros do estudo e os resultados relatados são revisados ​​pela National Library of Medicine (NLM) para garantir que atendam aos padrões específicos de controle de qualidade antes de serem publicados no site público.

Datas Principais do Estudo

Início do estudo (Real)

15 de outubro de 2025

Conclusão Primária (Estimado)

1 de março de 2028

Conclusão do estudo (Estimado)

1 de março de 2030

Datas de inscrição no estudo

Enviado pela primeira vez

11 de abril de 2025

Enviado pela primeira vez que atendeu aos critérios de CQ

11 de abril de 2025

Primeira postagem (Real)

18 de abril de 2025

Atualizações de registro de estudo

Última Atualização Postada (Real)

9 de novembro de 2026

Última atualização enviada que atendeu aos critérios de controle de qualidade

5 de novembro de 2026

Última verificação

1 de novembro de 2026

Mais Informações

Termos relacionados a este estudo

Outros números de identificação do estudo

  • 24-1192

Plano para dados de participantes individuais (IPD)

Planeja compartilhar dados de participantes individuais (IPD)?

SIM

Descrição do plano IPD

A de-identified dataset from this study will be deposited in the Patient-Centered Outcomes Data Repository (PCODR) housed at the Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan, in compliance with PCORI's Policy on Data Management and Data Sharing.

Informações sobre medicamentos e dispositivos, documentos de estudo

Estuda um medicamento regulamentado pela FDA dos EUA

Não

Estuda um produto de dispositivo regulamentado pela FDA dos EUA

Sim

produto fabricado e exportado dos EUA

Não

Essas informações foram obtidas diretamente do site clinicaltrials.gov sem nenhuma alteração. Se você tiver alguma solicitação para alterar, remover ou atualizar os detalhes do seu estudo, entre em contato com register@clinicaltrials.gov. Assim que uma alteração for implementada em clinicaltrials.gov, ela também será atualizada automaticamente em nosso site .